Real-time image processing of human face identification for home service robot

This paper presents a real-time image processing of human face identification for home service robot (HSR). This vision system is set up by two individual sub-systems. The first one is face detection and tracking sub-system based on adaptive skin detector, condensation filter with parallel computing...

Full description

Saved in:
Bibliographic Details
Main Authors: Ying-Hao Wang, Yen-Te Shih, Cheng, K., Chih-Jui Lin, Li, T. S.
Format: Conference Proceeding
Language:English
Subjects:
Face
Face detection
Face recognition
Hidden Markov models
Humans
Image color analysis
Skin
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 1176
container_issue
container_start_page 1171
container_title
container_volume
creator Ying-Hao Wang
Yen-Te Shih
Cheng, K.
Chih-Jui Lin
Li, T. S.
description This paper presents a real-time image processing of human face identification for home service robot (HSR). This vision system is set up by two individual sub-systems. The first one is face detection and tracking sub-system based on adaptive skin detector, condensation filter with parallel computing particles, and Haar-like classifier. And a simple and fast motion predictor is also proposed for face tracking. The second is face recognition system based on embedded HMM (EHMM) with parallel training and recognition procedures. In order to reach a fast, robust, efficient, this study used extensible parallel integrated vision system (PIVS). Finally, real-time experimental results on different humans in different unknown scenes demonstrate that the proposed PIVS is indeed feasible, simple and safe.
doi_str_mv 10.1109/SII.2011.6147615
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6147615</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6147615</ieee_id><sourcerecordid>6147615</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-70ebdb6f025d40885a0e90f237875151b57b716162338eafa3130469741dac313</originalsourceid><addsrcrecordid>eNpVkM1LAzEQxSMiKHXvgpf8A7tmks3XUYofhaKgvZfs7qSNdDclWQX_ewP20ncZ3vsxw_AIuQPWADD78LlaNZwBNAparUBekMpqA63UGiTn5vLMC3lNqpy_WJFSVnFzQ94-0B3qOYxIw-h2SI8p9phzmHY0err_Ht1EvesLHnCagw-9m0MsWUx0H8taxvQTCk-xi_MtufLukLE6zQXZPD9tlq_1-v1ltXxc18GyudYMu6FTnnE5tMwY6Rha5rnQRkuQ0EndaVCguBAGnXcCBGuV1S0Mri9mQe7_zwZE3B5TeT39bk8liD-Pa06N</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Real-time image processing of human face identification for home service robot</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Ying-Hao Wang ; Yen-Te Shih ; Cheng, K. ; Chih-Jui Lin ; Li, T. S.</creator><creatorcontrib>Ying-Hao Wang ; Yen-Te Shih ; Cheng, K. ; Chih-Jui Lin ; Li, T. S.</creatorcontrib><description>This paper presents a real-time image processing of human face identification for home service robot (HSR). This vision system is set up by two individual sub-systems. The first one is face detection and tracking sub-system based on adaptive skin detector, condensation filter with parallel computing particles, and Haar-like classifier. And a simple and fast motion predictor is also proposed for face tracking. The second is face recognition system based on embedded HMM (EHMM) with parallel training and recognition procedures. In order to reach a fast, robust, efficient, this study used extensible parallel integrated vision system (PIVS). Finally, real-time experimental results on different humans in different unknown scenes demonstrate that the proposed PIVS is indeed feasible, simple and safe.</description><identifier>ISBN: 9781457715235</identifier><identifier>ISBN: 1457715236</identifier><identifier>EISBN: 9781457715228</identifier><identifier>EISBN: 1457715228</identifier><identifier>EISBN: 9781457715242</identifier><identifier>EISBN: 1457715244</identifier><identifier>DOI: 10.1109/SII.2011.6147615</identifier><language>eng</language><publisher>IEEE</publisher><subject>Face ; Face detection ; Face recognition ; Hidden Markov models ; Humans ; Image color analysis ; Skin</subject><ispartof>2011 IEEE/SICE International Symposium on System Integration (SII), 2011, p.1171-1176</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6147615$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6147615$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ying-Hao Wang</creatorcontrib><creatorcontrib>Yen-Te Shih</creatorcontrib><creatorcontrib>Cheng, K.</creatorcontrib><creatorcontrib>Chih-Jui Lin</creatorcontrib><creatorcontrib>Li, T. S.</creatorcontrib><title>Real-time image processing of human face identification for home service robot</title><title>2011 IEEE/SICE International Symposium on System Integration (SII)</title><addtitle>SII</addtitle><description>This paper presents a real-time image processing of human face identification for home service robot (HSR). This vision system is set up by two individual sub-systems. The first one is face detection and tracking sub-system based on adaptive skin detector, condensation filter with parallel computing particles, and Haar-like classifier. And a simple and fast motion predictor is also proposed for face tracking. The second is face recognition system based on embedded HMM (EHMM) with parallel training and recognition procedures. In order to reach a fast, robust, efficient, this study used extensible parallel integrated vision system (PIVS). Finally, real-time experimental results on different humans in different unknown scenes demonstrate that the proposed PIVS is indeed feasible, simple and safe.</description><subject>Face</subject><subject>Face detection</subject><subject>Face recognition</subject><subject>Hidden Markov models</subject><subject>Humans</subject><subject>Image color analysis</subject><subject>Skin</subject><isbn>9781457715235</isbn><isbn>1457715236</isbn><isbn>9781457715228</isbn><isbn>1457715228</isbn><isbn>9781457715242</isbn><isbn>1457715244</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpVkM1LAzEQxSMiKHXvgpf8A7tmks3XUYofhaKgvZfs7qSNdDclWQX_ewP20ncZ3vsxw_AIuQPWADD78LlaNZwBNAparUBekMpqA63UGiTn5vLMC3lNqpy_WJFSVnFzQ94-0B3qOYxIw-h2SI8p9phzmHY0err_Ht1EvesLHnCagw-9m0MsWUx0H8taxvQTCk-xi_MtufLukLE6zQXZPD9tlq_1-v1ltXxc18GyudYMu6FTnnE5tMwY6Rha5rnQRkuQ0EndaVCguBAGnXcCBGuV1S0Mri9mQe7_zwZE3B5TeT39bk8liD-Pa06N</recordid><startdate>201112</startdate><enddate>201112</enddate><creator>Ying-Hao Wang</creator><creator>Yen-Te Shih</creator><creator>Cheng, K.</creator><creator>Chih-Jui Lin</creator><creator>Li, T. S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201112</creationdate><title>Real-time image processing of human face identification for home service robot</title><author>Ying-Hao Wang ; Yen-Te Shih ; Cheng, K. ; Chih-Jui Lin ; Li, T. S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-70ebdb6f025d40885a0e90f237875151b57b716162338eafa3130469741dac313</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Face</topic><topic>Face detection</topic><topic>Face recognition</topic><topic>Hidden Markov models</topic><topic>Humans</topic><topic>Image color analysis</topic><topic>Skin</topic><toplevel>online_resources</toplevel><creatorcontrib>Ying-Hao Wang</creatorcontrib><creatorcontrib>Yen-Te Shih</creatorcontrib><creatorcontrib>Cheng, K.</creatorcontrib><creatorcontrib>Chih-Jui Lin</creatorcontrib><creatorcontrib>Li, T. S.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore (Online service)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ying-Hao Wang</au><au>Yen-Te Shih</au><au>Cheng, K.</au><au>Chih-Jui Lin</au><au>Li, T. S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Real-time image processing of human face identification for home service robot</atitle><btitle>2011 IEEE/SICE International Symposium on System Integration (SII)</btitle><stitle>SII</stitle><date>2011-12</date><risdate>2011</risdate><spage>1171</spage><epage>1176</epage><pages>1171-1176</pages><isbn>9781457715235</isbn><isbn>1457715236</isbn><eisbn>9781457715228</eisbn><eisbn>1457715228</eisbn><eisbn>9781457715242</eisbn><eisbn>1457715244</eisbn><abstract>This paper presents a real-time image processing of human face identification for home service robot (HSR). This vision system is set up by two individual sub-systems. The first one is face detection and tracking sub-system based on adaptive skin detector, condensation filter with parallel computing particles, and Haar-like classifier. And a simple and fast motion predictor is also proposed for face tracking. The second is face recognition system based on embedded HMM (EHMM) with parallel training and recognition procedures. In order to reach a fast, robust, efficient, this study used extensible parallel integrated vision system (PIVS). Finally, real-time experimental results on different humans in different unknown scenes demonstrate that the proposed PIVS is indeed feasible, simple and safe.</abstract><pub>IEEE</pub><doi>10.1109/SII.2011.6147615</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 9781457715235
ispartof 2011 IEEE/SICE International Symposium on System Integration (SII), 2011, p.1171-1176
issn
language eng
recordid cdi_ieee_primary_6147615
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Face
Face detection
Face recognition
Hidden Markov models
Humans
Image color analysis
Skin
title Real-time image processing of human face identification for home service robot
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T20%3A46%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Real-time%20image%20processing%20of%20human%20face%20identification%20for%20home%20service%20robot&rft.btitle=2011%20IEEE/SICE%20International%20Symposium%20on%20System%20Integration%20(SII)&rft.au=Ying-Hao%20Wang&rft.date=2011-12&rft.spage=1171&rft.epage=1176&rft.pages=1171-1176&rft.isbn=9781457715235&rft.isbn_list=1457715236&rft_id=info:doi/10.1109/SII.2011.6147615&rft.eisbn=9781457715228&rft.eisbn_list=1457715228&rft.eisbn_list=9781457715242&rft.eisbn_list=1457715244&rft_dat=%3Cieee_6IE%3E6147615%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-70ebdb6f025d40885a0e90f237875151b57b716162338eafa3130469741dac313%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6147615&rfr_iscdi=true